Skip to main content
Log in

Structured Reactive Controllers

  • Published:
Autonomous Agents and Multi-Agent Systems Aims and scope Submit manuscript

Abstract

Service robots, such as autonomous office couriers or robot tourguides, must be both reliable and efficient. This requires them to flexibly interleave their tasks, exploit opportunities, quickly plan their course of action, and, if necessary, revise their intended activities. In this paper, we show how structured reactive controllers (SRCs) satisfy these requirements. The novel feature of SRCs is that they employ and reason about plans that specify and synchronize concurrent percept-driven behavior. Powerful control abstractions enable SRCs to integrate physical action, perception, planning, and communication in a uniform framework and to apply fast but imperfect computational methods without sacrificing reliability and flexibility. Concurrent plans are represented in a transparent and modular form so that automatic planning processes can reason about the plans and revise them. We present experiments in which SRCs are used to control two autonomous mobile robots. In one of them an SRC controlled the course of action of a museum tourguide robot that has operated for thirteen days, more than ninetyfour hours, completed 620 tours, and presented 2668 exhibits.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. T. Arbuckle and M. Beetz, “Extensible, runtime-configurable image processing on robots-the recipe system,” in Proc. 1999 IEEE/RSJ Int. Conf. Intell. Robots Sys., 1999.

  2. R. Alami, R. Chatila, S. Fleury, M. Ghallab, and F. Ingrand, “An architecture for autonomy,” Int. J. Robotics Res., 1998.

  3. M. Beetz, T. Arbuckle, A. Cremers, and M. Mann, “Transparent, flexible, and resource-adaptive image processing for autonomous service robots,” in H. Prade (ed.), Proc. 13th Eur. Conf. Artif. Intell. (ECAI-98), 1998, pp. 632-636.

  4. M. Beetz and M. Bennewitz, “Planning, scheduling, and plan execution for autonomous robot office couriers,” in R. Bergmann and A. Kott (ed.), Integrating Planning, Scheduling and Execution in Dynamic and Uncertain Environments, Workshop Notes 98-02, AAAI Press, 1998.

  5. M. Beetz, W. Burgard, D. Fox, and A. Cremers, “Integrating active localization into high-level control systems,” Robotics Auton. Syst., vol. 23, pp. 205-220, 1998.

    Google Scholar 

  6. M. Beetz, M. Bennewitz, and H. Grosskreutz, “Probabilistic, prediction-based schedule debugging for autonomous robot office couriers,” in Proc. 23rd German Conf. Artif. Intell. (KI 99), Bonn, Germany, Springer Verlag: Berlin, 1999.

    Google Scholar 

  7. W. Burgard, A. B. Cremers, D. Fox, D. Hähnel, G. Lakemeyer, D. Schulz, W. Steiner, and S. Thrun, “The interactive museum tour guide robot,” in Proc. Fifteenth Nat. Conf. Artif. Intell. (AAAI'98), 1998.

  8. P. Bonasso, J. Firby, E. Gat, D. Kortenkamp, D. Miller, and M. Slack, “Experiences with an architecture for intelligent, reactive agents,” J. Exp. Theor. Artif. Intell., vol. 9, no. 1, 1997.

  9. W. Burgard, D. Fox, and S. Thrun, “Active mobile robot localization,” in Proc. of the Fifteenth Int. Conf. Artif. Intell. (IJCAI-97), 1997.

  10. M. Beetz and H. Grosskreutz, “Causal models of mobile service robot behavior,” in Fourth Int. Conf. AI Planning Syst., p. 163, 1998.

  11. M. Beetz, M. Giesenschlag, R. Englert, E. Gülch, and A. B. Cremers, “Semi-automatic acquisition of symbolically-annotated 3D models of office environments,” in Int. Conf. Robotics Automat. (ICRA-99), 1999.

  12. M. Beetz and D. McDermott, “Declarative goals in reactive plans,” in J. Hendler (ed.), First Int. Conf. AI Planning Syst., Morgan Kaufmann: San Francisco, pp. 3-12, 1992.

  13. M. Beetz and D. McDermott, “Improving robot plans during their execution,” in K. Hammond (ed.), Second Int. Conf. AI Planning Syst., Morgan Kaufmann, San Francisco, pp. 3-12, 1994.

    Google Scholar 

  14. M. Beetz and D. McDermott, “Local planning of ongoing activities,” in B. Drabble (ed.), Third Int. Conf. AI Planning Syst., Morgan Kaufmann: San Francisco, pp. 19-26, 1996.

    Google Scholar 

  15. M. Beetz and D. McDermott, “Expressing transformations of structured reactive plans,” in Recent Advances in AI Planning: Proc. 1997 Eur. Conf. Planning, Springer Publishers, pp. 64-76, 1997.

  16. M. Beetz and H. Peters, “Structured reactive communication plansóintegrating conversational actions into high-level robot control systems,” in Proc. 22nd German Conf. Artif. Intell. (KI 98), Bremen, Germany, Springer Verlag: Berlin, 1998.

    Google Scholar 

  17. R. Brooks, “The behavior language: user's guide,” MIT Artif. Intell. Lab., Cambridge, MA, A.I. Memo 1227, 1990.

    Google Scholar 

  18. D. Fox, W. Burgard, and S. Thrun, “The dynamic window approach to collision avoidance,” IEEE Robotics Automat. Mag. 1997.

  19. J. Firby, “An investigation into reactive planning in complex domains,” in Proc. AAAI-87, Seattle, WA, pp. 202-206, 1987.

  20. J. Firby, “Adaptive execution in complex dynamic worlds,” Technical report 672, Department of Computer Science, Yale University, 1989.

  21. E. Gat, “ESL: a language for supporting robust plan execution in embedded autonomous agents,” in AAAI Fall Symp.: Issues Plan Execution, Cambridge, MA, 1996.

  22. M. Georgeff and F. Ingrand, “Decision making in an embedded reasing system,” in Proc. 11th IJCAI, Detroit, MI, pp. 972-978, 1989.

  23. L. Kaelbling, “Goals as parallel program specifications,” in Proc. AAAI-88, St. Paul, MN, pp. 60-65, 1988.

  24. D. Lyons and M. Arbib, “A formal model of computation for sensory-based robotics,” IEEE J. Robotics Automat. vol. 5, no. 3, pp. 280-293, 1989.

    Google Scholar 

  25. D. McDermott, “A reactive plan language,” Research Report YALEU/DCS/RR-864, Yale University, 1991.

  26. D. McDermott, “Transformational planning of reactive behavior,” Research Report YALEU/DCS/ RR-941, Yale University, 1992.

  27. B. Pell, D. Bernard, S. Chien, E. Gat, N. Muscettola, P. Nayak, M. Wagner, and B. Williams, “An autonomous spacecraft agent prototype,” in Proc. First Int. Conf. Auton. Agents, 1997.

  28. A. Rao and M. Georgeff., “An abstract architecture for rational agents,” in B. Nebel, C. Rich, and W. Swartout (ed.), Principles of Knowledge Representation and Reasoning: Proc. Third Int. Conf. (KR'92), Kaufmann: San Mateo, CA, pp. 439-449, 1992.

    Google Scholar 

  29. M. Schoppers, “Universal plans for reactive robots in unpredictable environments,” in Proc. Tenth Int. Joint Conf. Artif. Intell. (IJCAI-87), 1987.

  30. R. Simmons, R. Goodwin, K. Haigh, S. Koenig, J. O'Sullivan, and M. Veloso, “Xavier: Experience with a layered robot architecture,” ACM Mag. Intell. 1997.

  31. R. Simmons, “A robust layered control system for a mobile robot,” IEEE J. Robotics Automat., pp. 34-43, 1994.

  32. S. Thrun, A. Bücken, W. Burgard, D. Fox, T. Fröhlinghaus, D. Hennig, T. Hofmann, M. Krell, and T. Schmidt, “Map learning and high-speed navigation in Rhino,” in D. Kortenkamp, R. P. Bonasso, and R. Murphy (ed.), AI-Based Mobile Robots, MIT Press: Cambridge, MA, 1998.

    Google Scholar 

  33. S. Thrun, M. Bennewitz, W. Burgard, A. B. Cremers, F. Dellaert, D. Fox, D. Haehnel, C. Rosenberg, N. Roy, J. Schulte, and D. Schulz, “Minerva: a second generation mobile tour-guide robot,” in Proc. IEEE Int. Conf. Robotics Automat. (ICRA'99), 1999.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Beetz, M. Structured Reactive Controllers. Autonomous Agents and Multi-Agent Systems 4, 25–55 (2001). https://doi.org/10.1023/A:1010014712513

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1010014712513

Navigation